My understanding/experience is that LLM performance in a language scales with how well the language is represented in the training data.
From that assumption, we might expect LLMs to actually do better with an existing language for which more training code is available, even if that language is more complex and seems like it should be “harder” to understand.
As others said, the key is feedback and prompting. In a model with long context, it'll figure it out.